September 24, 2013

Mathematical Simulation Accurately Predicts Rise Of Complex Societies

A unique marriage of mathematics and history has helped researchers solve the mysteries surrounding the evolution of human society from small groups to the larger, more complex societies of the modern era.

A trans-disciplinary team of experts from the University of Connecticut, the University of Exeter in England, and the National Institute for Mathematical and Biological Synthesis (NIMBioS) have completed a cultural evolutionary model that accurately predicts when and where the largest-scale complex societies arose in human history. Their research appears this week in the journal Proceedings of the National Academy of Sciences.

“Simulated within a realistic landscape of the Afro-Eurasian landmass during 1,500 BCE to 1,500 CE, the mathematical model was tested against the historical record,” NIMBioS, an organization dedicated to solving basic and applied problems in the life sciences, explained in a statement. “During the time period, horse-related military innovations, such as chariots and cavalry, dominated warfare within Afro-Eurasia.”

They also discovered that geography played an important role in such developments, as nomads residing in the Eurasian Steppe helped influence societies that depended on agriculture for support and sustenance. By doing so, the study authors said that the nomads helped spread forms of offensive warfare into those agrarian societies.

“The study focuses on the interaction of ecology and geography as well as the spread of military innovations and predicts that selection for ultra-social institutions that allow for cooperation in huge groups of genetically unrelated individuals and large-scale complex states, is greater where warfare is more intense,” NIMBioS said.

“While existing theories on why there is so much variation in the ability of different human populations to construct viable states are usually formulated verbally, by contrast, the authors' work leads to sharply defined quantitative predictions, which can be tested empirically,” they added.

The authors reported that the spread of larger societies predicted by their simulation was very similar to the actual, observed proliferation. In fact, they stated that their mathematical model was able to explain two-thirds of the variation in determining the rise of large-scale societies.

“What's so exciting about this area of research is that instead of just telling stories or describing what occurred, we can now explain general historical patterns with quantitative accuracy,” said study co-author and NIMBioS director for scientific activities Sergey Gavrilets. “Explaining historical events helps us better understand the present, and ultimately may help us predict the future.”

In addition to Gavrilets, the authors of the paper include Peter Turchin of the University of Connecticut’s Department of Ecology and Evolutionary Biology, Thomas E. Currie of the University of Exeter’s Centre for Ecology and Conservation, and Edward A. L. Turner of South Woodham Ferrers, England. The study was edited by Charles S. Spencer of the American Museum of Natural History in New York.